Point Cloud Features. We sample 1024 points of point clouds for each object \(i\)  in the form of RGB-XYZ, denoted as \(pc_{i} \in \mathbb {R}^{1024 \times 6}\) . Then point cloud features \(\lbrace x_{1},\dots ,x_{M}\rbrace \)  for all objects are extracted by the object encoder (e.g. PointNet++ [1]}) and a linear mapping layer, given as:
\(x_{i} = \text{LN}(W_{x} \cdot \text{PointNet++}(pc_{i})),\) 
